| Summary: | This research sought to examine and evaluate geospatial predictive policing models across the United States. The purpose of this applied research is three-fold: (1) to link theory and appropriate data/measures to the practice of predictive policing; (2) to determine the accuracy of various predictive policing algorithms to include traditional hotspot analyses, regression-based analyses, and data-mining algorithms; and (3) to determine how algorithms perform in a predictive policing process. Specifically, the research project sought to answer questions such as: <ul> <li>What are the underlying criminological theories that guide the development of the algorithms and subsequent strategies? </li> <li> What data are needed in what capacity and when? </li> <li> What types of software and hardware are useful and necessary? </li> <li> How does predictive policing "work" in the field? What is the practical utility of it? </li> <li> How do we measure the impacts of predictive policing? </li> </ul> The project's primary phases included: (1) employing report card strategies to analyze, review and evaluate available data sources, software and analytic methods; (2) reviewing the literature on predictive tools and predictive strategies; and (3) evaluating how police agencies and researchers tested predictive algorithms and predictive policing processes.
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